1. Field of the Invention
This invention relates to the field of medical systems for helping patients make informed medical decisions, and more particularly to a computerized health evaluation system (CHES) that involves full patient participation in selecting among various treatment options for particular medical conditions and a shared decision-making process with a physician in order to allow the best possible medical treatment to be carried out, considering the patient""s lifestyle and other patient preferences along with that patient medical condition as entered by the physician and the most up-to-date medical data concerning that medical condition.
2. Description of the Prior Art
Many medical conditions have two or more treatment paths, each with generally different costs and different outcomes and risks depending on the patient""s particular circumstances. Included among these conditions is mitral valve disease. It is known that knowledge of direct and indirect treatment costs permits patients to assess the economic impact of their treatment choices and affects their treatment preferences. Moreover, it is known that cost-sharing lowers the overall utilization of the medical system. Accordingly, it may be that knowledge of treatment costs without an understanding of treatment effectiveness can negatively impact health.
There has been a considerable amount of research dedicated to the issue of the role of the patient in selecting a treatment choice. Studies indicate that patients tend to value their doctor""s recommendations more in cases with more severe or life-threatening conditions. However, patients generally wish to take part in medical decisions concerning their health.
In an era of rising medical costs and greater demands on physicians to deliver better care at a lower cost, many physicians, particularly those who do not specialize in particular diseases and conditions, are not always abreast of the most current medical findings and data. Even when physicians are fully aware of the various treatment options, they presently do not have the tools which allow them to work with their patients to help jointly select the best treatment based upon the latest statistical findings, cost factors, and their patient""s expressed lifestyle choices and preferences. Indeed, knowledge about diseases and their treatments is expanding faster than can be absorbed. Compounding this fact is the diversity in interpreting medical knowledge due to physician differences in training, experience, and peer influence. To be most effective, a physician should be aware of all available information. This calls for clinician access to up-to-date information services such as computer data banks.
Each possible treatment for a given condition has a unique clinical and non-clinical impact. One way to evaluate outcomes for treatment effectively before selecting one is to use economic rules which explain human needs and behavior. As used here, the term xe2x80x9ceconomicxe2x80x9d includes monetary costs, the values of other factors, and opportunity costs which differ with each patient. These rules can be used to rate one""s desires and priorities, to identify a preferred solution. Since one solution may not be ideal as other possible solutions, a way to access all possible solutions is needed to reveal the one which will achieve the optimal outcome.
Computers can be programmed with specific data management rules. These rules need validation by collecting treatment outcome data from the medical literature; statistically analyzing them to verify diverse practice patterns for the same condition; and having medical experts in each area interpret these results. These experts can provide a consensus on the dynamics of a disease and the implications of its different forms of treatment. They can also help identify which clinical parameters would indicate when major intervention is actually needed.
With these rules, computers can be used to assess each patient""s status and how it may be uniquely impacted by each treatment. This evaluation must include a broad range of data that cannot be manually collected and assimilated for each patient. Thus, consistency is achieved by using computers to repeat complex tasks with equal accuracy. This permits reliability in the analysis and in formatting of the results without human error.
Computers cannot fully answer questions dealing with clinical, economic, family concerns, and other varied issues. They can, however, manage data on these issues, expressly: what numeric measure to give to certain data, what data sets to use, what values to compute, and with what formulas. Computers can also be encoded to format its assessment in a printout of information that can be easily interpreted. The computerized health evaluation system CHES of the invention uses these capabilities in its systems.
Under the approach of the invention, the patient can input individual information and concerns/desires, and the physician will input clinical data and a preliminary treatment plan, if any, for the patient. Thus, the patient will more actively be participating in the decision making process, yet still maintain his or her doctor""s position on treatment.
Three major parties are affected by the selection of a given treatment. Each has inadequate information with which to optimize their xe2x80x9creturnxe2x80x9d from the treatment of a given medical condition. The following is a summary of the issues they face:
A. The Problem:
1. Patients
This consumer has limited clinical knowledge. The patient often does not know what questions to ask when a diagnosis is made and a treatment is recommended. S/He will not know all of the treatment options. Trying to consider non-clinical risks linked to both the condition and each possible treatment adds to the confusion. For example, what are the true trade-offs in delaying treatment? What are the potential negative consequences of a given treatment to a patient""s family and career, and their probability of occurring? Patients often have no means to assess these issues in the context of their unique circumstances.
2. Physicians
The physician diagnoses and prescribes treatments, but often has little time to inform the patient about the possible effects of the condition, all possible treatments, and their potential positive and negative outcomes. The physician also may not know every non-clinical factor of each patient that may affect the choice of treatment. He must make critical decisions under much uncertainty. These uncertainties, (e.g. surgical risks, treatment outcomes, non-clinical impact), and the concerns of the patient, (e.g. impact on family, income loss) complicate the decision-making process. Thus, an unsuitable treatment may be selected without a mechanism for identifying, measuring, or fully assessing all relevant factors.
3. Third Party Payer (Insures/Employers)
These entities are outside the clinical decision-making process to avoid a conflict of interest. However, they are directly affected by treatment decisions due to their high costs, especially from poor outcomes. Recent California legislation allows insurers to confirm the need for hospitalization (Pre-Admission certification). Yet, there is no systematic way to verify what treatments are the most appropriate both clinically and economically.
B. Attempted Solutions:
To address these issues, various studies are now under way to identify the most effective treatments for given conditions based on outcomes. This outcomes research will set new practice patterns regarding treatments. This has some value in emphasizing outcomes over the process or structure of health care as a measure of quality. There is a risk, however, of strictly using treatments deemed most clinically effective, instead of offering treatments based on what each patient needs, clinically and non-clinically. Since patients are not identical, the most effective treatment is that which offers clinical improvement, and preserves quality of life, which differs in each case.
Efforts to identify unnecessary treatments is now popular in trying to reduce health care costs by withholding coverage for such treatments, unless physicians can justify their use. While these limits can generate short-term cost savings, such efforts intrude on the physician-patient relationship, and can be harmful if the condition requires the treatment, but does not meet a set criteria. Since each patient is unique, with different needs beyond his/her clinical status, rationing treatments based on strict criteria often raises health care costs and lowers patient satisfaction.
In-patient ancillary services have also been restricted, again based on predetermined criteria. If there is little flexibility for complications during stays, or if extending the stay is not properly justified, the patient is again jeopardized. The question is whether to control costs by limiting the use of resources, or whether to improve the chances that the patient is receiving the correct and timely treatment. The latter would reduce costs by avoiding morbidity or mortality resulting from improper treatment and/or restricted use of health care resources.
Limiting services emphasizes the process of health care rather than outcomes (e.g. extended survival, reduced morbidity, or increased productivity of the patient), which are not considered when services are sought or paid for. This is because the issues involved appear too diverse and complex in relation to one another to allow their careful consideration as part of the decision-making process. Since current technology has not been filly exploited in complex problem analysis, rudimentary, restrictive criteria are used to control costs, without assessing a treatment""s value in terms of its short- and long-term effects relative to its alternatives.
There accordingly remains a need for a tool designed to help patients reach the best treatment options taking into consideration the patient""s lifestyle and personal choices, the cost and effectiveness, and the physician""s by assessing each option in terms of patient specific data.
One object of the present invention is to provide a tool designed to help patients reach the best treatment options taking into consideration the patient""s lifestyle and personal choices, the cost and effectiveness, and the physician""s assessment of each option in terms of patient specific data.
Another object of the invention is to provide a medical decision system wherein the patient can input individual information and concerns/desires, and the physician will input clinical data and a preliminary treatment plan, if any, for the patient, to develop various treatment options with the costs and benefits.
Yet another aspects of the invention is to provide a computerized health evaluation system which allows for full patient participation in treatment selection and a shared decision-making process with physicians in order to choose among different costs and post-treatment outcomes.
The computerized health evaluation system permits the patient""s unique circumstances, as determined by the physician and patient to be are entered into the system. This information is processed by the system which has statistical information about the particular medical condition, the various treatment options, the treatment effectiveness, financial impact, and current disease-related data from the medical literature. The system outputs a report which presents the various kinds of information for evaluation by the patient and doctor for a discussion and review session. The system then allows complex medical decisions to be made more effectively and with more confidence.
These and other objects of the invention are provided by the system which i) includes a large patient role in treatment choice based upon the patient""s lifestyle and other choices, ii) patient/physician shared decision making, iii) patient/physician communication, iv) patient education and informing, and v) computer technology to facilitate decision discussion and the decision-making process.
These and other objections of the invention are described with reference to mitral valve disease, as an example. Mitral valve disease presently has two surgical treatment approaches with different financial costs and outcomes associated with each of the two procedures. The method of the invention is applicable to any number of medical conditions having multiple treatment regimens, including, for example, prostate cancer, breast cancer.